Achievement Growth in K-8 Catholic Schools Using NWEA Data

Using a national sample of kindergarten to eighth grade students from Catholic and public schools who took MAP Growth assessments, we examine achievement growth over time between sectors. Our findings suggest that while Catholic school students score higher in math and reading than public school students on average, they also enter each school year at a higher level. Public school students close this gap to some degree during the school year. Additionally, these patterns varied by age and subject. Catholic school students in the earlier grades show less growth in both reading and math during the academic year compared to their public school peers, but in middle school growth patterns in math were comparable across sectors.

Excellence in medical training: developing talent—not sorting it

Many medical schools have reconsidered or eliminated clerkship grades and honor society memberships. National testing organizations announced plans to eliminate numerical scoring for the United States Medical Licensing Examination Step 1 in favor of pass/fail results. These changes have led some faculty to wonder: “How will we recognize and reward excellence?” Excellence in undergraduate medical education has long been defined by high grades, top test scores, honor society memberships, and publication records. However, this model of learner excellence is misaligned with how students learn or what society values. This accolade-driven view of excellence is perpetuated by assessments that are based on gestalt impressions influenced by similarity between evaluators and students, and assessments that are often restricted to a limited number of traditional skill domains. To achieve a new model of learner excellence that values the trainee’s achievement, growth, and responsiveness to feedback across multiple domains, we must envision a new model of teacher excellence. Such teachers would have a growth mindset toward assessing competencies and learning new competencies. Actualizing true learner excellence will require teachers to change from evaluators who conduct assessments of learning to coaches who do assessment for learning. Schools will also need to establish policies and structures that foster a culture that supports this change. In this new paradigm, a teacher’s core duty is to develop talent rather than sort it.

Status, Growth, and Perceptions of School Quality

States and districts are increasingly incorporating measures of achievement growth into their school accountability systems, but there is little research on how these changes affect the public’s perceptions of school quality. We conduct a nationally representative online survey experiment to identify the effects of providing participants with information about their local public schools’ average achievement status and/or average achievement growth. Prior to receiving any information, participants already possess a modest understanding of how their local schools perform in terms of status, but they are largely unaware of how these schools perform in terms of growth. Participants who live in higher status districts tend to grade their local schools more favorably. The provision of status information does not fundamentally change this relationship. The provision of growth information, however, alters Americans’ views about local educational performance. Once informed, participants’ evaluations of their local schools better reflect the variation in district growth.

Lord–Wingersky Algorithm Version 2.5 with Applications

Item response theory scoring based on summed scores is employed frequently in the practice of educational and psychological measurement. Lord and Wingersky (Appl Psychol Meas 8(4):453–461, 1984) proposed a recursive algorithm to compute the summed score likelihood. Cai (Psychometrika 80(2):535–559, 2015) extended the original Lord–Wingersky algorithm to the case of two-tier multidimensional item factor models and called it Lord–Wingersky algorithm Version 2.0. The 2.0 algorithm utilizes dimension reduction to efficiently compute summed score likelihoods associated with the general dimensions in the model. The output of the algorithm is useful for various purposes, for example, scoring, scale alignment, and model fit checking. In the research reported here, a further extension to the Lord–Wingersky algorithm 2.0 is proposed. The new algorithm, which we call Lord–Wingersky algorithm Version 2.5, yields the summed score likelihoods for all latent variables in the model conditional on observed score combinations. The proposed algorithm is illustrated with empirical data for three potential application areas: (a) describing achievement growth using score combinations across adjacent grades, (b) identification of noteworthy subscores for reporting, and (c) detection of aberrant responses.

Value-added in Higher Education: a new methodology for undergraduate programs in Brazil

Among the quality indicators released by the Brazilian Higher Education Assessment System (Sinaes), the Indicator “Difference between Observed and Expected Performance” (IDD) has the purpose of measuring the contribution of the course to student achievement during undergraduate programs. The research presented here offers a new methodology for calculating the IDD (Model IDD-VDCF), examining the philosophical and statistical underpinnings of quality measures, focusing on those that capture the value-added as a student achievement growth. The survey included a sample of 30,668 students, from 911 accounting undergraduate programs in Brazil. The insertion of control variables (at the student and at the institution level) reduced the bias of the IDD estimate associated with the student's selection in specific Accounting Sciences courses. The results call attention to the need to consider the students' learning context when one wants to compare the performance between institutions based on standardized tests. The major contribution of this work is the development of a measure that disentangles more fully what the contribution of program is to student learning, and what merely is a reflection of the capacity that a student brought to the program.

The impact of COVID-19 on student learning in New South Wales primary schools: an empirical study

The COVID-19 pandemic produced widespread disruption to schooling, impacting 90% of the world’s students and moving entire school systems to remote and online learning. In the state of New South Wales, Australia, most students engaged in learning from home for at least eight weeks, with subsequent individual and intermittent school closures. However, while numerous claims have circulated in the popular media and in think tank reports, internationally, about the negative impacts on learning, there is limited empirical evidence of decreased student achievement. Drawing on data from more than 4800 Year 3 and 4 students from 113 NSW government schools, this paper compares student achievement during 2019 and 2020 in a sample of matched schools to examine the effects of the system-wide disruption. Somewhat surprisingly, our analysis found no significant differences between 2019 and 2020 in student achievement growth as measured by progressive achievement tests in mathematics or reading. A more nuanced picture emerges when the sample is examined by dis/advantage (ICSEA) and Year level. The Year 3 cohort in the least advantaged schools (ICSEA < 950) achieved 2 months less growth in mathematics, while the Year 3 students in mid-ICSEA schools (950–1050) achieved 2 months’ additional growth. No significant differences were identified for Indigenous students or students located in regional locations. These results provide an important counter-narrative to widespread speculation about alarming levels of ‘learning loss’ for all students. While the lower achievement growth in mathematics for Year 3 students in lower ICSEA schools must be addressed as a matter of urgency to avoid further inequities, most students are, academically, where they are expected to be. Our findings are a testament to the dedicated work of teachers during the 2020 pandemic to ensure that learning for most students was not compromised, despite unusually trying circumstances.

Do Schools Reduce or Exacerbate Inequality? How the Associations Between Student Achievement and Achievement Growth Influence Our Understanding of the Role of Schooling

This article explores how the associations between student achievement and achievement growth influence our understanding of the role schools play in academic inequality. Using nationally representative data from the Early Childhood Longitudinal Study, Kindergarten Class of 2010–2011 (ECLS-K:2011), we constructed parallel growth and lagged score models within both seasonal learning and school effects frameworks to study how student- and school-level socioeconomic and racial/ethnic backgrounds relate to student learning. Our findings suggest that seasonal comparative scholars, who generally argue that schools play an equalizing role, and scholars focused on school compositional effects, who typically report that schools exacerbate inequality, come to these contrasting findings not only because they ask different questions but also because they treat student initial achievement differently when modeling student learning.